The Industrial Internet of plastics


Predictions concerning the economic impact of the Industrial Internet, also known as the Internet of Things (IoT), are simply staggering. One estimate suggests a boost to global GDP by as much as $10-15 trillion over the next 20 years, [Source: The Industrial Internet@Work, General Electric]. The hype behind the Industrial Internet stems from its unique ability to create new efficiencies and accelerate growth in productivity. The plastics sector, which represents the third largest manufacturing industry in the United States, stands to benefit significantly from the improved efficiencies enabled by IoT. Plastics facilities that integrate IoT solutions into their remote monitoring activities can see value added to their operations through three interrelated dimensions: enhanced data gathering, advanced analytics and remote service.

Data gathering

Evaluating efficiency must go beyond measuring a specific machine's uptime if manufacturers want to understand how well their entire operation works together at all stages of production. The interconnection of internet-enabled machines allows for a new level of accessibility to machine data. For the manufacturing of plastic materials and components - a particularly technical operation - this data is critical. Those looking to improve their process and find new efficiencies can utilize data to provide a clearer picture of their operations as a whole. Furthermore, through the utilization of wireless systems and cloud based storage services, even greater amounts of information can be collected with less hardware across the facility.


A massive amount of information is born from this enhanced connectivity. Yet the data is only useful to the degree it can be understood and turned actionable. Sophisticated analytics afford the ability to do so by directly transforming information into valuable performance indicators. Overall Equipment Effectiveness (OEE) can be calculated automatically by applying hard data to the OEE formula (Availability X Performance X Quality). Combining the capabilities of these analytics with an on-site display platform, such as a Productivity Display, allows operators to fully leverage the machine's data in real time on the factory floor.

Manufacturers can take a step further by putting in place predictive algorithms that are able to identify a problem and take an action before any person sees the data. At this point a facility's equipment becomes proactive, adjusting controls like temperature or pressure as needed to prevent a problem from occurring. This proactive capability can be applied to equipment wear and tear as well, predicting an equipment failure before it occurs and automatically ordering the necessary part. These abilities preempt failures on the line, greatly reducing downtime and waste, and in turn increasing productivity and profitability.
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